OT/IT Connectivity with Vortex Edge Connect

One of the main challenges facing the Industrial Internet of Things (IIoT) community is connecting operational or field systems, comprised of devices and other data sources utilizing a diverse range of protocols with higher level Internet of Things (IoT) systems. This is where Vortex Edge Connect comes in.

Vortex Edge Connect ingests data from industrial devices such as PLCs, PAC, RTUs, DAQs, sensors, actuators, etc. using a range of Operational Technology (OT) protocols. This ingested data is then converted into a normalized in-memory data model which enables this data to be shared with other higher level systems such as SCADA systems, analytics engines, ERP, MES, etc.

Due to the Vortex Edge Connects innovative design, it is highly scalable and can support 1-to-1, 1-to-many, or many-to-many data connection models. Whether you’re in a Linux or Windows environment, Vortex Edge Connect is platform and operating system independent, enabling you to deploy with ease and peace of mind for expansion and integration.

For more information on Vortex Edge Connect, please visit our website.

Getting Started Tutorial with Vortex OpenSplice Tester Video

In this tutorial video presented by Nate Wieselquist, you can learn about how to get started using the Vortex OpenSplice Tester tool in order to help you automate the process of testing and debugging your DDS system. Both passive and active benefits of the Vortex OpenSplice Tester tool are covered in this video as well as an example walkthrough.

MathWorks MATLAB and Simulink with Vortex OpenSplice DDS Tutorial

To coincide with the release of PrismTech’s Vortex OpenSplice 6.8, we have put together a series of videos to show how simple using Vortex OpenSplice DDS in MATLAB and Simulink is.

Presented by Paul Elder, these videos walk you through everything you’ll need to get up and running with Vortex: from installation, right through to building a model.

 

Getting Smarter at the Edge

With over 2 billion people around the world now users of a smartphone, we have more computing power than ever right at our fingertips than ever before. Our cars, houses, factories, cities, etc. are all becoming smarter too. With all of this distributed computing power and applications, we’re producing and consuming vast quantities of data … but are we using this data effectively?

As systems grow in complexity and the number of connected devices/sensors increases, so too does the sheer volume of data produced. That is a lot of (potentially sensitive) data to be sending to the cloud to be analyzed for faults/abnormalities. Then there is the issue of network connectivity: what if the network goes down? What if the latency is too high for the safety/mission/business critical scenario? There are many single points of failure in a cloud-reliant solution. Local computing is therefore still vitally important to many industries, but this data still has value. Aggregating this data at the edge for cloud analysis is one way in which companies can derive massive business benefits without overburdening network communications. This aggregate data can be analyzed for insights, and results deployed back down to the edge.

Automation is an area in which edge computing plays a vital role: when you need an action to be taken immediately should something happen; you require a low-latency instantaneous response. Running edge based analytics enables companies to perform reactive, predictive, and prescriptive actions in real-time with no bandwidth costs or WAN networking issues to worry about. Automating decisions at the edge enables geographically isolated systems to benefit from big-data analytics without requiring high-bandwidth, low-latency connections to the cloud.

Edge computing is enabling many areas of high interest: self-driving cars, factory automation, autonomous drones, predictive maintenance, and the list keeps growing. Unlocking the potential of the ever-growing volume of data being produced means greater efficiency, more effective and timely actions, and valuable insights.

The recently announced Vortex Edge PMQ solution utilizes the power of PrismTech’s Vortex data-connectivity software, ADLINK’s ruggedized industrial hardware, and IBM’s advanced Predictive Maintenance and Quality analytics. Vortex Edge PMQ provides an edge analytics solution designed for Industrial Internet of Things environments where cloud computing access may be limited or otherwise not desired.

For a more detailed look at Vortex Edge PMQ and implementation examples, visit http://www.prismtech.com/vortex/vortex-edge-pmq